Corporate Social Responsibility (CSR) has emerged as a critical factor influencing the reputation and long-term success of organizations in today’s competitive business environment. This study aims to examine the perception of Chartered Accountants regarding the role of CSR in enhancing the goodwill of companies. Given their professional expertise in financial management, auditing, and corporate governance, Chartered Accountants hold a unique perspective on how CSR initiatives contribute to stakeholder trust, ethical business practices, and brand value. A sample of 179 Chartered Accountants from Ahmedabad city was surveyed using a structured questionnaire based on a Likert scale to capture their perceptions. The findings reveal a strong consensus among respondents that CSR initiatives significantly enhance the overall reputation of companies. Chartered Accountants perceive that companies engaging actively in CSR are considered more trustworthy by stakeholders, thereby strengthening their credibility in the market. Moreover, the study indicates that CSR activities contribute substantially to long-term goodwill and the enhancement of brand value, highlighting CSR as not just a legal or ethical obligation but also a strategic tool for sustainable organizational growth. The research underscores the role of Chartered Accountants in guiding and monitoring CSR practices to ensure transparency, accountability, and alignment with corporate objectives. Overall, the study establishes a clear link between CSR practices and corporate goodwill, emphasizing that socially responsible initiatives are integral to building stakeholder confidence and promoting ethical corporate behavior. The insights from Chartered Accountants offer valuable guidance for organizations seeking to design effective CSR strategies that enhance reputation, trust, and long-term value creation.

A person who is widely recognised and famous, often because of their exploits in fields such as entertainment, sports, or politics, is called a celebrity.  In marketing terms, an endorsement is an action by a person, mostly a celebrity, who publicly approves and promotes a product as being of high quality or desirable (McCracken, 1989). CE combines these elements, utilising a famous individual's public approval to enhance a product's image and appeal to consumers. Bergkvist & Zhou (2016) defined celebrity endorsement as the engagement of an individual with public recognition to promote an entity (a brand or a social cause). CE involves a mutually beneficial relationship, where celebrities earn by lending their image and boost the brand attractiveness of products and services (Al Mamun et al., 2023; Silva et al., 2015).

Access to agricultural credit plays a crucial role in enhancing farm productivity and financial stability. This study examines the influence of procedural challenges, access to financial services, credit usefulness, and social influence on farmers’ perceptions of agricultural loans. Using a quantitative research approach, data were collected from 426 farmers across selected districts, and independent sample t-tests were conducted using SPSS to analyze the differences among demographic groups. The findings reveal that female farmers face greater challenges in securing agricultural loans due to collateral requirements and institutional biases. Married farmers have better financial access and higher confidence in loan utilization, while joint family farmers rely more on family opinions for financial decisions compared to those from nuclear families. The study highlights the need for policy interventions focusing on gender-inclusive credit schemes, financial literacy programs, and customized loan structures that consider socio-demographic factors

The paper focuses on how organizational psychology could be applied to enhance the problem-solving behaviour at work places in the United Arab Emirates (UAE). The issues of time-bound economic diversification, multicultural workforce and shifting business demands are placing companies in tricky situations, and these issues must be tackled in innovative and planned manners. Organizational psychology provides a paradigm through which the behaviours of employees including their motivation and the interrelationship among others can be understood and therefore helps organizations to provide a conducive environment that facilitates good decision making and conflict resolution. The paper highlights how psychological constructs such as cognitive flexibility, emotion intelligence and motivation theories can help identify the causal factors of the challenges at workplace, and how solutions to the same can be developed so that they are sustainable. It pays attention to the specific cultural and organisational context in the UAE where diversity and cross-cultural relations are the most important elements in the daily business. The case study examines cultural responsive leadership, employee engagement and practiced approaches and structured communication channels that facilitate cooperation, and problem-solving capability in the workplace across sectors. The methodological foundation of the paper relies on the literature, case studies and practices in the UAE context, relating the psychological theories to the practices in the organization development. The findings have revealed that the organizations that have involved psychological insights in the working practices have improved team cohesion, employee satisfaction and better conflict resolution. Furthermore, organizational psychologists contribution to training process, resilience, and change management guidance may also be pointed out as a major contributor to the suffering of productivity amid the changing environment.This paper has demonstrated that the contribution of organizational psychology cannot be overstated in terms of its strategic importance to the UAE organizations so that they are able to counter the challenges in the most efficient manner possible, as well as instilling innovation and adaptability. The lessons can be used in the real field of practice and the academic world to offer ideas to the leader, human resource practitioners, and policymakers on how the problem-solving strategy can be refined to operate in different workplace settings.

This paper examines the critical role of digital literacy among senior citizens in India, highlighting challenges, gaps, and opportunities for inclusion in the digital era. Drawing from literature and field research, the study presents findings from the Sach ke Saathi digital literacy program and assesses its impact on media consumption, information verification, and socio-cultural engagement of elderly participants. Policy and academic implications are discussed, emphasizing the need for targeted interventions to bridge the digital divide and protect older adults from misinformation, cyber risks, and social isolation.

The introduction of Artificial Intelligence (AI) in the sphere of education has provoked the emergence of new patterns of pedagogy, and flipped classroom became one of the most significant approaches that can transform a traditional pattern of learning. This paper will comment on the overlap between AI technologies and the flipped classroom strategy and propose a new model of learning that will enhance the learning process of an individual, engagement with students, and teaching effectiveness. A deeper conceptual learning and problem solving can be realized through this paradigm by reversing the conventional instructional sequences whereby the instructional contents are taught outside in the classroom and active learning in the classroom. AI products in the field of intelligent tutoring, adaptive learning systems, and data analytics can allow educators to personalize the content according to the profile of a specific learner, monitor their progress, and respond to the needs of that learner. This research is characterized by a mixed-method design because it utilizes an element of quantitative research of performance measures of students, along with qualitative data of teacher and student feedbacks in different learning environments. The results have demonstrated that the academic performance, motivation, and self-regulated learning practices of AI-enhanced flipped classrooms have a significant positive impact, and it also reduces the cognitive load of the face-to-face classes. Further, AI is also implemented to aid predictive analytics to find at-risk students and balance curriculum pacing to address the long-standing problem of differentiated instruction. Theoretical limitations that the research may face are also examined in the study including privacy of data, access to technology, and training in the use of AI among teachers. Overall, the findings can be used to point to the implications of AI-enhanced flipped classrooms as a versatile and scalable model of pedagogy. The model offers a sustainable model of education in the 21st century because the education process could be focused on active learning in the form of personalized and engaging experiences, instead of teaching a passive content, which is appropriate to the needs of digital literacy and lifelong learning and competencies in the new labour market.

This rapid increasing remote workforce has introduced unique challenges in the management of an increasingly dispersed workforce, often referred to as the invisible workforce. It is impossible to sustain engagement, productivity, and organizational commitment of remote workers according to the face-to-face interaction model by relying on conventional Human Resource Management (HRM) tactics, which will be implemented on-site. This paper will examine the contemporary HRM practices that are channelled towards promotion of engagement, motivation, and performance in virtual workplaces. The paper takes into account the theoretical insights of literature on the organizational behaviour and remote work and enumerates the major bases that influence the engagement of the remote employees including quality of communication, technological systems, leadership practices, and organizational culture. The paper also discusses the interventions of HRM such as the policies of flexible work, virtual team building programs, digital recognition programs, and continuous feedback programs which enhance psychological safety and a sense of belonging among remote workers. Within a mixed methodology, the research would combine the knowledge of surveys and interviews and case-studies in a variety of industries to present the comprehensive view of the best engagement practices. These results prove that the HR managers should employ proactive, technology-based, and individual approaches that consider problematic and personal needs of remote workers. Moreover, the paper focuses on the strategic importance of HR to meet the organizational objectives along with personal well-being, work-life balance, and eradication of loneliness. Lastly, a practical framework is also presented in the paper that offers the HR professional a chance to develop, execute, and take into account strategies of engagement, which are adaptable to evolving remote work models. The article contributes to the existing body of literature about the virtual workforce management by offering evidence-based recommendations that would enhance the performance of organizations and retain employees, as they would be satisfied, loyal, and committed to their work in the post-pandemic, digitally connected workplace.

The increasing global attention to sustainability has also affected the manner in which business companies articulate their policy towards the environment. Contrary to the concept of green marketing which, through actual identification of real environmental engaging initiatives, is built on, greenwashing is founded on false marketing disregarding exaggeration and forming unrealistic profits on the environment. The paper discusses how the consumers view the two practices and how the practices impact consumer trust in the brand. The study uses the available literatures and the empirical evidence to identify the significance of transparency, credibility and consistency in the sustainability messages to consumer judgment. The results suggest that more consumers are becoming more and more sceptical of environmental claims and are likely to be questioning themselves whether companies are motivated by actual responsibility, or are simply attempting to control their image. In the analysis, it is evident that greenwashing is a large aspect of killing trust, the brand equity in the long term, and developing consumer backlash. Quite the contrary, a true green marketing would enhance credibility, loyalty of the customers, and it will make companies appear as social responsibility leaders. The paper also looks at how the moderating variables such as consumer awareness, previous brand reputation and third-party certifications influence alterations in perceptions. Findings indicate that educated customers are more qualified with their discernment skills in differentiating between genuine and deceptive and this increases the reputational risks of greenwashing. The paper concludes that in the age of more sustainability awareness companies need to give a lot of consideration to transparency, verifiable practices and open communication to maintain trust. After this distinct differentiation between the real sustainability actions and the lies, this research contributes to the existing knowledge about the influence of consumer perception on brand trust in an environmentally oriented marketing. The applied implications indicate that organizations are advised to use the quantifiable approaches of sustainability, external auditing, and open communication to ensure that there is credibility in the green communication accountability.

In this paper, the researcher will discuss how Artificial Intelligence (AI) is transforming educational marketing by creating hyper-personalized learning experiences to attract and retain students in a constantly competitive academic world. By using machine learning, recommendation engines, chatbots and data driven segmentation, all institutions are no longer content to merely carry out advertising but are also now able to predict behaviour and tailor content, as well serve learning pathways dynamically. The manuscript entails combined qualitative and quantitative research of 15 colleges in three countries (India, the US, and the UK) that employ surveys, web analytics (CRM) and AI-enhanced engagement tools to measure the effectiveness of personalized online experiences on enrolment and satisfaction. AI tools such as Python-based natural language processing (NLP), clustering algorithms, and neural recommender systems were used to review sentiment analysis, engagement metrics, as well as dropout prediction models. The findings are that personalized learning materials and adaptive feedback cycles lead to a massive rise in both long-term interest and decision to enrol, as chatbot-mediated interaction resulted in a 21 percent conversion increase in leads and adaptive course recommendations led to a 18 percent dropout decrease. It has been concluded that AI is not a mere tool of automation, it is an input strategic to lead the way to custom educational experiences that tighten institutional branding, user devotion and student results.

The rapid growth of e-commerce has intensified the need for efficient supply chain management (SCM) strategies to meet dynamic customer demands and reduce operational costs. This research investigates the application of machine learning (ML) algorithms—Linear Regression, Random Forest, Long Short-Term Memory (LSTM) networks, and K-Means clustering—to optimize demand forecasting, inventory management, and logistics in e-commerce SCM. Historical transaction data comprising 50,000 orders across 500 products were analyzed, and models were trained to predict demand, manage stock levels, and optimize delivery routes. Experimental results indicate that LSTM networks achieved the highest accuracy in demand forecasting with a prediction error of less than 1%, significantly outperforming Linear Regression (error ~3%). The accuracy of the inventory prediction by the random forest was 94. 25, which guaranteed the timely delivery of goods and a reduced risk on overstock. K-Means was the clustering algorithm that minimized the average distance of the delivery by 15 percent, which allowed good distribution of warehouses and organization of logistics. Comparative studies involving the current research [15 26] reveal that the experimental approach of integrating the ML-based framework would raise efficiency of operations involved, cut down costs and elevate customers satisfaction. Findings have indicated that optimization of the SM with the help of machine learning has potential to mobilize smart, dynamic, and resilient supply chains in the e-commerce.

The change of curriculum management is gradually happening through the use of Artificial Intelligence (AI) in enhancing quality of education and marketing efficiency. The paper discusses the application of AI algorithms (Decision Tree, random Forest, support vector machine (SVM), and K-Nearest Neighbors (KNN) to predict performance, prescribe to students (what courses they enroll), and how high education can be marketed in a better way. They were compared using a sample of 1,000 student data in 20 courses (attendance, engagement, completion of assignments, grades, and marketing interactions). It is observed that random Forest recorded the best prediction on academic performance at 91, SVM recorded the highest at 88, Decision Tree at 85 and KNN at 82. The KNN had an improved outcome on personalized course recommendation with F1-score of 0.86 and in this case the result used by the Random Forest was 0.835. Prediction of the marketing response showed that the prediction of Random Forest is efficient and achieves accuracy reaching to 89 percent of success in detecting such influential features as their engagement score, their use of marketing channel and their prior enrollment behaviour. The feature importance analysis revealed that the engagement score (0.35), the attendance (0.30) count as essential to the academic success and the marketing channel (0.35) or previous enrollment (0.25) is significant to the responsiveness. It has shown that AI-based curriculum management leads to the improvement of the learning performance, personal learning, and data-based marketing planning that help to give an organization the map upon which the organization operation optimization should occur and the greater the interaction with students.

The present project navigates the practical landscape of TinyML, offering a guided tour through training and deployment phases of machine learning models—specifically those intended for resource-poor microcontrollers. TinyML, in most cases, supports energy-efficient, low-latency inference, which renders it well-suited to edge devices that demand real-time decisions independent of cloud connectivity. The core of this study revolves around three specific applications showcasing the adaptability and usefulness of TinyML: Animal Sound Classification, Human Recognition, and Voice-Controlled RGB Lighting. Generally speaking, these applications cross several domains—smart homes, personalized devices, and even pet monitoring—effectively demonstrating how TinyML can infuse intelligent features into common, inexpensive hardware [10]. Moreover, the project considers the intrinsic difficulties inherent in training models with small datasets, optimizing them for constrained deployment, and maintaining real-time performance under strict power and memory limitations. This practical exploration into TinyML presents valuable insights into the complete model lifecycle, ranging from data preprocessing and initial collection to model optimization, training, and final inference. In doing so, this work offers a thorough, practical framework for researchers and developers seeking to integrate machine learning into the quickly evolving IoT and embedded systems fields. Noteworthy is the analysis of how effectively techniques like parameter quantization and interpolation are in enhancing model efficiency and improving performance on devices with substantially restricted resources, as seen in related research.

This study investigates the impact of Trade Openness, Investment, Human Capital, and Infrastructure Development on GDP growth. Utilizing regression analysis on secondary data from Mumbai, the findings reveal that Trade Openness and Investment significantly contribute to GDP growth, while Infrastructure Development shows no significant effect. The analysis highlights the critical role of Trade Openness and Investment in enhancing economic performance and suggests that these factors should be prioritized in economic policy-making. The study contributes to the understanding of economic growth drivers and offers implications for both national and global economic strategies. Future research could expand on these findings by exploring different contexts or examining the interaction between these variables.

Today banking is known as innovative banking. Computer technology has given rise to new innovations in the product designing and their delivery in the banking and finance industries. The enormous advances in technology and artificial intelligence sector had been developing at an exceptional quickness and is being applied in many walks of life. The aggressive infusion of information or computer technology like Artificial intelligence had brought in a radical shift in banking operations and is received with enthusiasm due to its capability of taking human-like decisions and avoiding humanlike errors. The concept and scope of Artificial Intelligence is ever evolving. It promotes an effective payment and accounting system thereby enhancing the speed of delivery of banking services considerably. Due to Artificial Intelligence, there is raise in customer satisfaction level, reduction in cost of banking operations, increased productivity and as such there is a great scope for Indian banks to enlarge their tech banking services which could enhance their competitiveness. It entails high levels of automation and web-based services. The paper suggests some measures to tackle the AI based challenges faced by the banks particularly public sector banks.

This research examines the situational factor effects on women's entrepreneurial intentions in India and underscores their pivotal role in economic progress. Entrepreneurship increases productivity and standards of living as well as solving social problems. Women contribute significantly to economic development in a developing nation such as India. The United Nations Sustainable Development Goals emphasized gender equality and empower women and girls as its fifth goal. Different push and pull factors impacting women's intention to start their own businesses are emphasized and researched by various scholars. Situational factor as a component of push factor has scanty literature to examine its effect on women's entrepreneurial intention. This study targets specific situational factors such as fear of unemployment, contribution to family income and well-being and family commitment and its effect on women's desire to start their own businesses.  204 Female students from different universities that provide entrepreneurship as a component of the curriculum are considered as study population.

The emerging economies women entrepreneurs play a very significant role in enhancing the economic growth, innovation as well as social development. These women are particularly constrained in structure, culture and finance to carry out their entrepreneurial activities despite their capabilities. In this paper, the issues that are complex to women entrepreneurs will be addressed including inaccessibility to capital, gender bias institutional structures, social movement and decision-making restrictions, and gaps of the professional network. According to the qualitative and quantitative facts on different emerging economies, the study can unearth the differences in how such barriers vary in their cultural, regional and sectorial context. At the same time, the paper establishes bridges that favour the entrepreneurial performance of women. Access to formal and informal support systems, mentorship programs, online platforms and accessibility of financial tools all become important enablers. Policies and ecosystem in gender equity and entrepreneurial training have been shown to have measurable impacts in increasing participation and business performance. It is also shown in the study that the agency of the individual, perseverance and adaptive mechanisms contribute to the surmounting of systemic constraints. Finally, the paper will discuss the case studies of breakthroughs where entrepreneurial experience of women has not only managed to rise to challenges but also made use of the opportunity to develop businesses, influence policy and generate social and economic effects of a community-wide scope. The examples may provide some teachings about what can be introduced to create a more friendly entrepreneurial atmosphere. The paper contributes to the understated opinion of the factors affecting the businesswoman activities of women in any emerging economy by introducing obstacles, bridging and breakthrough outcomes; the paper offers practical recommendations to policy makers, finance institutions and development professionals who are interested in realizing equal and sustainable entrepreneurship. The findings prove that empowerment of women entrepreneurs consists of a combination of structural change, particular support systems, and the recognition of innovativeness potential.

The contemporary work environment is undergoing a radical shift with the rise of representatives of Generation Z (Gen Z) employees who have their values, expectations, and behavioural patterns. This work analyses how Emotional Intelligence (EI) is critical to the successful work and interaction with the Gen Z workforce. Self-awareness, self-regulation, motivation, empathy and social skills are enumerated as crucial aspects of Emotional Intelligence that leaders and managers ought to possess as crucial competences in order to deal with diverse challenges in the workspace. The study of the role of EI in communication, conflict management, teamwork, and overall performance of Gen Z employees involves a combination of quantitative survey and a qualitative interview by the researcher in different industries. The findings have indicated that managers having a high EI score are better placed to meet the needs of the Gen Z employees who desire to be offered with meaningful work, flexible schedules and positive feedback. Such managers provide an inclusive and supportive organizational environment that enhances job satisfaction, reduces turnover intentions, and organizational commitment. Besides, active listening, emotional coaching, and individualized mentorship are also named the EI-based measures that can be effective in the process of overcoming generational differences and motivating younger workers (see the study). It is also mentioned in the study that the training interventions on EI should be included in the organization development projects, and it is not the leadership approach alone that the resiliency and flexibility of Gen Z teams. Practical implications on human resource practitioners, team managers, and organizational policymakers who seek to maximize engagement and performance in the rapidly evolving work environment are provided in the paper through bringing out the overlapping of emotional intelligence and managing generational workforce. Lastly, the research article is contributing to the current literature on the dynamics of generational workforce and the role of EI in attaining sustainable productivity, ideal work culture, and sustainable success of an organization.

Cloud adoption continues to grow across industries, offering scalability, flexibility, and operational efficiency. However, uncontrolled cloud spending presents significant challenges. This research investigates cost optimization strategies for two leading cloud platforms, Microsoft Azure and Amazon Web Services (AWS). By analyzing existing literature, evaluating cost management tools, and reviewing empirical case studies, the study provides a comprehensive understanding of how businesses can reduce their cloud expenditures. The primary focus is on key cost-saving strategies, such as resource rightsizing, leveraging provider discounts, storage optimization, and the use of automation tools powered by artificial intelligence (AI) and machine learning (ML). It also highlights challenges faced by organizations in implementing effective cost optimization strategies, including complex billing models and unpredictable workloads. Case studies, including real-world examples from organizations such as Discovery, show that significant savings are achievable through strategic use of reserved instances, tiered storage, and auto-scaling. Furthermore, this research explores the future of cloud cost optimization, emphasizing the increasing role of AI-driven optimization techniques. The findings suggest that, by adopting best practices for cost control, businesses can maximize the value of their cloud investments, ultimately transforming cloud expenditure from a cost burden into a competitive advantage.

In this rapidly transforming economic era owing to the changes and the necessities brought in my numerous reasons after the COVID-19 years, India has recently made significant changes to its revenue policies, ease of doing business, taxation policies and is now focusing on increasing its economic environment. Farfetched initiatives have been taken in order to deal with the notices, compliance requirements, filings, assessments and appellate proceedings with regard to taxation proceedings. These proceedings in the present regime are done through technological contributors such as Income Tax Portals, E-mails or social networking websites in order to to reduce the extent of physical interface of the taxpayers with their Jurisdictional Departmental officer. The pace of reaching to a conclusion w.r.t Taxation proceedings in the Faceless assessments and appeals regime is much quicker and convenient now and its all because of the aid and ease provided by technology. Under the faceless assessment system, a taxpayer or an assessee is not required to visit an I-T department office or meet a department official for income tax-related dealings rather the process has been made much easier, quicker and convenient. The faceless assessment scheme was launched in 2019 with the objective to promote an efficient and effective tax administration by minimizing physical interface and increasing accountability & introduction of team-based assessments. Faceless assessment is administered through separate units within the tax department each of which have a specific and important role in the process, viz assessment units, verification units, technical units and review units. We can find that the Faceless Assessment/Appellate Scheme was introduced mainly keeping in mind various factors eg. corruption, quality of assessments, harassment of taxpayers and reduction of various time-lags etc. This research makes an attempt to analyze, whether this ongoing faceless regime in Direct Tax mechanism of India is in line with the compliance of Principle of Natural Justice given under Article 14 and Article 21 of Constitution the of India. This study analyses the various High Court pronouncements under WRIT Jurisdiction under articles 226 and 227 of the Constitution of India, regarding protection of Principles of Natural Justice as per Article 14 and Article 21 of Constitution the of India.  Since the said faceless laws is very new and its nascent stage, this law needs to pass the litmus test under the four corner-pillars of law. In this research paper, the authors analyse orders passed by various High Courts under WRIT jurisdiction under 226 of constitution of India.  Initially, there was some gross violation of Principles of Natural Justice on mass level and various High Courts remanded back the cases with some very serious and adverse remarks against Income Tax Authorities regarding their functioning and not following the Principles of Natural Justice.  Various High Courts tried to cater immediate problems/issues which arises under said the Faceless Scheme of Assessment and Appellate Proceedings in Indian Income Tax Act, 1961.

In today’s dynamic digital ecosystem, influencer marketing has emerged as a pivotal strategy for shaping brand awareness and purchase decisions, particularly among Generation Z and Millennials. This study explores the influence of key influencer persona attributes Authentic Vulnerability (AV), Narrative Creativity (NC), Ethical Alignment (EA), Interaction Personalization (IP), and Platform Fit (PF) on two critical marketing outcomes: brand awareness and purchase decision. Drawing on an empirical quantitative approach, data was collected from 50 respondents through a structured questionnaire and analyzed using multiple linear regression. The findings reveal that all five influencer characteristics significantly and positively affect brand awareness, with Platform Fit and Narrative Creativity showing the highest standardized beta coefficients. Similarly, these variables also have a statistically significant influence on purchase decisions, underscoring the role of emotionally authentic, ethically aligned, and creatively engaging content in driving consumer behavior. The study’s conceptual framework and tested hypotheses offer a refined model for understanding how influencer traits translate into marketing impact, moving beyond conventional metrics such as follower count or reach. The results highlight the importance of strategic influencer-brand alignment and the nuanced expectations of digital-native consumers, who prioritize trust, relatability, and platform-specific content relevance. These insights are particularly valuable for marketers in designing targeted influencer campaigns and for scholars interested in the behavioral dynamics of influencer marketing. Overall, the research provides both theoretical enrichment and practical guidance in leveraging influencer persona design for heightened brand performance among Gen Z and Millennial cohorts.

Limited useable urban land is a problem in many densely populated Indian cities, and the constructed heritage may be at danger throughout the rebuilding process. Improvements to the built environment and social wellbeing may come with significant costs and financial loss, especially in cities where land is highly valued. Managing socio-environmental objectives alongside economic benefits in urban revitalization continues to be difficult. To enable private redevelopment, clear and effective mechanisms are crucial. Transferable Development Rights (TDR) provide an organizational approach that aligns public and private interests while facilitating infrastructure development in the face of land limitations. Nonetheless, the lack of market transparency, changes in demand, and intricate regulations frequently hinder its efficiency. This study examines the TDR market in Mumbai, concentrating on demand-side dynamics, developer choices, regulatory and spatial influences, and the impact of digital implementation. Through qualitative insights, the research illustrates how project and site-specific factors influence developer choices. Essential elements affecting market responsiveness encompass infrastructure preparedness, regulatory transparency, risk tolerance, and site preference. The results guide specific policy and practical modelling to improve market efficiency and promote sustainable growth. Digital platforms can revolutionize TDR transactions and better align them with changing urban demands through real-time tracking, clear pricing, and simplified approvals.

The increasing pressure to ensure that the environment is made sustainable has generated the need to reconsider the role played by the human resource management in ensuring the ecological responsibility is created. The green Human Resource Management (GHRM) practices have evolved as a strategic practice that could result to congruence of the workforce management with sustainability through the incorporation of the environmental values into the recruitment, training, performance appraisal and reward systems. The paper targets the ways in which the organizational green policies can be successfully transferred into the actual change in the practices of the employees and how vital the formal initiatives can be in the process, and how critical is the individual move. The paper addresses the components of the awareness, motivation and accountability of the employees as the policies including environmentally friendly training, green performance indicators and incentives systems are used to generate awareness delivering through the existing literatures and case experience. It is also transposed to the organizational culture and leadership as the initiator of green norms and psychological motivators of the employee willingness to embrace the practice of being pro-environmentally friendly at the workplace. The results indicate that the frames of the policies are an obligatory condition, but the success of these frameworks depends to a great extent on the regularity of communication, the involvement of the employees, and the introduction of the green practices to the routine working process. Moreover, the behaviour change is enabled through the long-term perspective by the occupation with personal values and long-term sustainability goals of the organization. The paper finds out that GHRM is not merely a compliance apparatus, yet it can be a transformational apparatus that would enable the employees to be active participants in the environmental performance. The organizations will be capable of taking long-range measures in the direction of the sustainable development, and they will also be able to enhance their image and competitiveness in the environment of scarce resources.

The sustained success and growth of an organization are intrinsically linked to the performance of its employees, which is significantly influenced by the degree of their engagement. Employee engagement has emerged as a critical construct with the potential to enhance employee retention, foster higher levels of productivity, and strengthen organizational loyalty. The present study, drawing upon primary data collected through a structured questionnaire, establishes that the level of employee engagement within organizations is contingent upon multiple factors, namely job satisfaction, financial benefits, opportunities for career development, and the overall working environment. The implications of these findings are particularly pertinent for human resource professionals seeking to design and implement strategies that nurture long-term employee commitment while simultaneously mitigating attrition. Such efforts are essential to improving organizational performance within the Indian banking sector.

Digital transformation has emerged as one of the major promoters of economic growth especially in emerging economies whereby technological revolution is transforming industries, governance and social systems. The article discusses the connection between digital transformation and economic growth through the lens of significant variables like development of infrastructure, digital financial systems, e-governance, smart industry practices, development of human capital, policy and regulatory support and mobile connectivity. In the study, 250 respondents were sampled under a convenient sampling technique and the statistics were assessed with descriptive statistics and inferential statistics, such as independent t-tests and chi-square tests. Results indicate that digital financial systems, e-governance and policy support is seen as the most impactful force of economic transformation, with infrastructure gaps, skills shortages, cyber security issues, and digital divides being perceived to slow progress. There were observed gender differences in the perceptions of some challenges, but none of them were significant. The findings indicate that long-term economic development in emerging economies is not only based on the use of technology, but also on the reinforcement of human capital and policies. This research highlights the importance of governments, enterprises, and institutions to spend strategically on digital infrastructure and skills training in order to reap the most out of the digital transformation towards inclusive and sustainable growth.

In the digital age, artificial intelligence (AI) has transformed marketing by enabling brands to deliver personalized, data-driven, and emotionally engaging experiences. Emotional branding, traditionally based on human connection, storytelling, and identity creation, is now being reshaped by AI tools such as chatbots, virtual assistants, recommendation algorithms, and generative content. This paper examines how AI-powered emotional branding influences consumer trust and perceptions of authenticity. The study uses primary data collected from 150 respondents across various age groups and professional backgrounds. A structured questionnaire assessed consumer perceptions of AI-enabled branding practices, trust levels, and authenticity concerns. Statistical methods like frequency analysis, percentages, and chi-square tests analyzed the data. Brands must, therefore, find a balance between automation and human authenticity. The study concludes that successful emotional branding in the AI era depends on transparency, ethical AI use, and combining human creativity with machine intelligence. The research adds value to both academic literature and managerial practice by offering insights into the changing dynamics of branding in the AI era, providing a guide for marketers to build trust while staying authentic in emotionally driven brand strategies.

Nepal has a very high gender inequality index, which needs to be improved through gender empowerment measures index in the areas of politics, workforce, and resources.  The data for 1990-2023 reveal that Nepal’s progress in gender empowerment measure indices far exceeds the targets for 2030, but the gender inequality index is far behind the milestones set for it, and is not anywhere near the target for 2030.   This is because of a weak correlation between GII and GEM, where a unit increase in GEM contributed to reducing GII with a coefficient of -0.49 only. So a survey with the women political leaders (N=836, n=224) from municipal wards to federal parliament provided several policy choices to improve the GEM in its magnitude, quality, and equity. Accordingly, the ratings by political leaders on a scale of 10-1 for the pre-specified 31 strategies, the top-five strategies for better GEM are: address gender wage gaps, improve educational access and quality, amend election laws, mainstream deprived women of various social identities, and make political parties fair and democratic. The study offers many such strategies for a strategic action plan on gender equality through improved gender empowerment measures.

Cloud kitchens are food service business that offers ready-to-eat meals for delivery or takeout ordered by phone, food delivery apps, websites, or through social networks. These businesses are around for many years but they become popular due to technological advances.With this in mind the present study was taken to examine the factors responsible for influencing the customers towards cloud kitchen. The study also analysed the role played by social media in the success of cloud kitchens. It is to know the extent of awareness created by social media. To test this objective a random sample of 500 customers were taken by the method of convenience. As the questionnaire was categorical in nature, chi-square test was conducted to check the significance of objectives. The study concludes that ‘Quality’ as a factor has pervasively influenced the customer and ‘Youtube’ as a social media was consistent in creating customer awareness towards the cloud kitchen. 

The entry of artificial intelligence (AI) into marketing has accelerated this transformation. From predictive analytics to recommendation systems, AI-enabled solutions have improved customer targeting, optimized marketing spend, and personalized content delivery (Dwivedi et al., 2021). Many Indian companies struggle with issues such as data quality, ethical concerns, integration challenges, and regulatory uncertainties. These barriers highlight the need for a framework that can help firms systematically harness the power of generative AI in marketing. Indian firms ranging from MNCs like Amazon India and Hindustan Unilever to startups like Swiggy and Paytm rely on search engine marketing (SEM), social media campaigns, and influencer marketing to drive customer acquisition. The COVID-19 pandemic further accelerated this trend, forcing even traditional sectors (e.g., education, healthcare) to adopt digital-first marketing. Technology Acceptance Model (TAM), and Diffusion of Innovations (DOI), the study developed and validated a seven-stage roadmap—from defining aims to deployment—that enables firms to systematically adopt Gen AI in marketinge.

Efficient invoice management is a critical component of financial operations in organizations, directly influencing cash flow, compliance, and overall operational efficiency. This study explores the implementation of a Peer-to-Peer Vendor Invoice Management (P2P VIM) system at Amara Raja Energy & Mobility Limited. The research focuses on the system's design, deployment, and effectiveness in streamlining invoice processing, reducing manual errors, and ensuring timely payments. Key features of the P2P VIM system, such as automated invoice matching, real-time tracking, and integration with existing ERP frameworks, are analyzed. Additionally, the study evaluates the system's impact on supplier relationships, internal productivity, and financial transparency. Findings highlight the challenges faced during implementation and the solutions adopted to overcome them. The paper concludes with recommendations for further optimization of the P2P VIM system to meet dynamic business needs and improve organizational efficiency.

Connections with stakeholders in the ever-changing digital ecosystem. Social media tactics are being used more and more in the higher education industry to recruit skilled teachers and staff, build employer branding, and draw in students. Platforms like LinkedIn, Facebook, Instagram, and X are strategic ways for higher education institutions to highlight their values, workplace culture, academic environment, and growth opportunities in a time when digital presence has a direct impact on institutional reputation. Beyond academic achievement and rankings, employer branding in higher education refers to the institution's capacity to establish itself as a preferred employer. Institutions may showcase inclusion, innovation, research possibilities, and staff well-being through social media storytelling, digital marketing, and interactive interaction. Candidates' attitudes and career decisions are greatly influenced by this visibility. However, attracting talent in the digital age necessitates a proactive strategy in which organizations match their online tactics to the demands of a workforce that is digitally savvy and seeks transparency, authenticity, and career advancement. The purpose of this study is to investigate how social media tactics affect higher education institutions' ability to attract talent and build their employer brands. It looks into how digital engagement strategies help ensure long-term competitiveness, draw in top-notch academics and staff, and increase institutional legitimacy. The research also looks at the best practices, difficulties, and new trends in using social media into HRM. It is anticipated that the results will offer significant perspectives to higher education administrators and policymakers, emphasizing the pivotal function of social media in molding enduring talent management tactics in the digital age.

Inflation is a persistent economic phenomenon that significantly impacts pricing strategies across various industrial sectors in India. This article explores the role of inflation in shaping pricing models within Indian industries by analyzing its types, key drivers, and effects on cost components such as raw materials, labor, and energy. The study highlights the challenges faced by businesses in an inflationary environment, including rising input costs, consumer price sensitivity, and contract rigidity. It also examines the strategic responses adopted by industries, such as dynamic pricing, shrinkflation, cost optimization, and supply chain diversification. Furthermore, the paper underscores the importance of government policies and monetary measures in stabilizing inflation and influencing pricing decisions. While inflation presents considerable challenges, it also offers opportunities for innovation, technological adoption, and financial risk management. The findings suggest that businesses that adapt through strategic pricing models, operational efficiencies, and product diversification are better equipped to sustain growth in an inflation-prone economy.

This study investigates the demographic profiles (age, education, and gender) of employees in General Manager, Assistant General Manager, and Debit Collection Officer roles within a financial institution and examines their perceptions regarding the sector-wise contribution to Non-Performing Assets (NPAs). Findings reveal a dominant 30–40-year age group across roles, varying educational attainment with professional qualifications high among Assistant General Managers and undergraduate degrees more common in Debit Collection, and a relatively balanced gender distribution with some role-specific skews. Perceptions of NPA origins differed by role, with General Managers emphasizing the Household sector, Assistant General Managers the Service sector, and Debit Collection Officers highlighting both Industrial and Household sectors. These disparities underscore the influence of job function on the understanding of NPA drivers. The study highlights the importance of considering both workforce demographics and internal perspectives on financial risk for effective management strategies.

In the rapidly evolving landscape of online Retail, integrating Virtual Reality and Augmented Reality technologies has transformed the shift from traditional e-commerce to immersive v-commerce, particularly gaining speed in the COVID-19 pandemic. The study evaluates consumer awareness of VR try-on features, assesses shopping experiences, and identifies perceived benefits and challenges. .it also indicates that Augmented Reality (AR) and Virtual Reality (VR) significantly enhance user engagement and satisfaction by allowing consumers to visualize clothes in a real-time manner, which helps to reduce return rates and increase purchase confidence. This study provides insights for retailers on leveraging immersive technologies to enhance customer experiences and increase sales, which shows the importance of understanding consumer perceptions in the evolving digital marketplace.

Amidst the algorithmically accelerated saturation of digital marketplaces, influencer-mediated persuasion has become a dominant force in shaping consumer psychology and market dynamics. This study offers a theoretically grounded and empirically validated exploration of how influencer credibility, content consistency, and relatability function as antecedents to consumer trust, which subsequently catalyses engagement and drives purchase intention. Utilizing Structural Equation Modelling on data gathered from 300 active users across Instagram, YouTube, and Snapchat, the research constructs a multi-stage behavioural framework that foregrounds trust and engagement as sequential mediators. Findings reveal that while influencer credibility exerts the most significant effect on trust, the translation of trust into engagement—and subsequently, into purchasing behavior—is profoundly moderated by platform dynamics. Specifically, long-form content platforms such as YouTube amplify the trust-engagement nexus more effectively than ephemeral short-form environments like Snapchat, suggesting that narrative depth and perceived authenticity intensify persuasive outcomes. The study enriches existing literature by integrating parasocial interaction theory and source credibility frameworks into a cohesive trust-engagement-purchase intention model, offering a robust lens for understanding influencer marketing efficacy. Practically, it directs marketers toward crafting platform-contingent strategies that privilege authentic interaction and longitudinal credibility over transient reach or superficial aesthetics. As digital influence evolves into a complex socio-commercial phenomenon, this work underscores the imperative of aligning content form, influencer behavior, and audience psychology to optimize consumer engagement and behavioural conversion.

Family efficacy refers to a family’s belief in its collective ability to achieve desired outcomes. It emphasizes the extent to which family members—parents, children, and spouses—can work together by pooling their resources, skills, and efforts. A family functions as a system with unique rules, roles, communication patterns, values, trust, faith, sacrifice, acceptance, and responsibilities that extend beyond individual members.

According to Kao and Caldwell (2017), family efficacy reflects the belief and confidence that family members can positively impact their children’s education, highlighting the role of parental involvement both at home and within the school environment.

This research is focused on the possibilities of Artificial Intelligence (AI) and analytics to bring innovation to Human Resources (HR) and sustainable financial growth in an organization. Based on the theories of Resource-Based Views, Human Capital Theory and Sustainable Growth Theory, the study investigates how AI-informed HR analytics support talent acquisition, employee engagement, performance management and workforce planning. The results have shown that inclusion of AI in the recruitment processes enhances the efficiency of the recruitment by 35%, its workforce improvement by 18% and a reduction in the cost of operation of the HR department by 22%. The long-term profitability is enhanced through these improvements in that they aligned the HR strategies with long organizational priorities, maximized on the use of resources, and developed the culture of the continuous improvement. Additionally, the paper also discusses proactive decision-making through predictive analytics, which reduce the cost of turnover and improve the organization to become more agile. Nonetheless, the ethical considerations, data quality, regulatory requirements, and employee resistance are the challenges that have to be overcome so that maximum benefits can be achieved. One of the AI and analytical study findings emphasizes the role of AI and analytics as strategic enablers rather than operational tools that enable the HR to push the competitive advantage and drive the issues of transparency, inclusivity, sustainable growth, etc. The paper ends with explanations of how AI in HR could be incorporated using sound ethical governance, data management and adaptation to industry needs to attain organizational stability and financial stability in the long run.

Index investing has long been popular in developed markets and is now gaining significant traction in developing economies like India, as investors seek cost-effective, diversified investment options. While traditional index funds provide broad market exposure, momentum investing gives an added edge by capitalizing on market trends, offering the potential for enhanced returns. Though momentum strategies are not ideal for risk-averse investors or those with short-term financial needs, they can serve as a high-growth component in a well-diversified portfolio for those comfortable with periodic rebalancing. This study examines the performance of momentum investing compared to traditional market indices, highlighting how momentum indices like Nifty 200 Momentum 30 and Nifty Midcap 150 Momentum 50 consistently outperform benchmarks such as Nifty 50, Nifty Midcap 150, and Nifty 200 over three-year and five-year rolling periods. While momentum investing offers higher returns, it comes with increased volatility, making it more suitable for investors with a long-term horizon and a higher risk appetite. A t-test assuming unequal variances confirms that the superior performance of momentum indices is statistically significant, indicating that the excess returns are not due to chance. Additionally, over a five-year period, momentum indices never recorded negative rolling CAGR, unlike broader indices, reinforcing the importance of staying invested for the long term.

Decision-making has changed a lot in this digital age. This increase in UGC on social media affected tourism because people increasingly relied on social media reviews for travel plans. Today, when planning a trip, most travellers rely upon the opinions and experiences of fellow travellers on the Web. The reason is the large number of UGCs on various social media platforms like Instagram, X, Facebook, and YouTube. Travel blogs, videos, photos, and reviews, among others, are shared by travellers in real-time, and the information can be quickly accessed by other people with internet access. It is important to note that social media reviews greatly influence other people's travel decisions. No matter what age they are, people believe in the opinions of others more than they believe in any form of advertising. In this context, previous studies have found that most travellers like to read reviews before deciding. User-generated content provides authenticity and transparency, which advertisements cannot portray. People can analysed feedback from fellow travellers to decide on their travel plans. Though subjective, other people's opinions and experiences are very informative regarding places, attractions, hotels, and activities one may want to visit or experience. Besides, connecting with other travellers through social media nowadays is very easy, and it helps a person make inquiries and ask for recommendations from real people who have undergone the same experience. Therefore, UGC posts on social media are very crucial in decision-making. Data was collected from 100 youngsters in India and analysed using SPSS software to determine the role of user-generated social media content. Factor analysis results identified 3 factors that influence decisions: Trust and credibility, Risk, and ease of use. The main objective was to identify the types of user-generated content that influence adventure travel decisions among youngsters and to know young traveller’s most commonly used social media platforms for adventure tourism information. 

The rising frequency of business insolvencies underscores the critical need for advanced predictive tools that offer real-time risk assessment. Traditional bankruptcy prediction models, which primarily depend on retrospective financial statement data, often fail to provide timely insights due to reporting delays and data incompleteness. This study proposes a machine learning-based framework for proactive bankruptcy prediction, leveraging ensemble learning techniques for greater accuracy and reliability. The analysis draws on a robust dataset comprising 2,800 firm-year observations from companies listed on the Bombay Stock Exchange (BSE) over the period 2020 to 2025. Quarterly financial indicators and market-based variables were systematically compiled to ensure comprehensive coverage of firm performance. To enhance model performance and mitigate overfitting, three advanced ensemble algorithms—XGBoost, AdaBoost, and Random Forest—were implemented. These models combine bagging and boosting mechanisms to optimize predictive capabilities. Recursive Feature Elimination (RFE) was used to identify the most significant predictors influencing financial distress. The study empirically tested four hypotheses: liquidity constraints as indicators of distress; operational cash flow deficits correlating with default risk; high debt-to-equity ratios signaling instability; and declining return on assets (ROA) as an early warning sign. The results demonstrate that the ensemble-based approach delivers high classification accuracy, with key variables conforming to recognized financial risk indicators. The findings highlight the potential of machine learning models to serve as early detection tools, aiding firms and investors in strategic decision-making. This research emphasizes the transformative role of artificial intelligence in improving financial risk management systems, enabling more dynamic and informed responses to emerging threats of bankruptcy.

The practice of financial organisations implementing socially and environmentally responsible strategies is known as "green banking." It entails offering financial services and products to promote eco-friendly projects. Green banks use energy-efficient operations and reduce paper waste, among other measures, to lessen their environmental effect. By incentivising consumers and businesses to adopt eco-friendly activities, they want to encourage sustainability. Ultimately, green banking unites the banking industry with initiatives to mitigate climate change and save natural resources. (Karthikeyan et al.,2018) Green banking practices are defined as electronic goods and services promoting environmentally friendly activities, such as electronic waste management systems, power consumption reduction, and eco-friendly operations. (Ganesan et al.,2016) Although the banking industry is not thought to be polluting, change is urgently needed. Green banking is a broad approach that integrates environmental factors into every facet of the banking sector. This study has taken Scopus as a citation database to conduct the bibliometric analysis.